Papers with hierarchical structure enhances learning

1 papers
Structural Supervision Improves Learning of Non-Local Grammatical Dependencies (N19-1)

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Challenge: State-of-the-art LSTM language models learn sequential contingencies with some success . LS models fail to learn other non-local grammatical dependencies, however .
Approach: They compare LSTM language models with RNNGs to examine grammatical dependencies . they find that hierarchical supervision improves learning of non-local dependencies.
Outcome: The proposed model outperforms the existing model on non-local dependencies and learns many of the Island Constraints on the filler-gap dependency.

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